The present invention relates to computed tomography imaging systems and methods and, more particularly, the invention relates to dual-source, dual-energy computed tomography.
In a current computed tomography system, an x-ray source projects a fan-shaped beam that is collimated to lie within an X-Y plane of a Cartesian coordinate system, termed the “imaging plane.” The x-ray beam passes through the object being imaged, such as a medical patient, and impinges upon an array of radiation detectors. The intensity of the radiation received by each detector is dependent upon the attenuation of the x-ray beam by the object and each detector produces a separate electrical signal that relates to the attenuation of the beam. The linear attenuation coefficient is the parameter that describes how the intensity of the x-rays changes when passing through an object. Often, the “mass attenuation coefficient” is utilized because it does not change with the density of the material. The attenuation measurements from all the detectors are acquired separately to produce the transmission map.
The source and detector array in a conventional CT system are rotated on a gantry within the imaging plane and around the object so that the projection angle at which the x-ray beam intersects the object constantly changes. A group of x-ray attenuation measurements from the detector array at a given angle is referred to as a “view” and a “scan” of the object. These views are collected to form a set of views made at different angular orientations during one or several revolutions of the x-ray source and detector. In a two dimensional (2D) scan, data is processed to construct an image that corresponds to a 2D slice taken through the object. The prevailing method for reconstructing an image from 2D data is referred to in the art as the filtered backprojection (FBP) technique. This process converts the attenuation measurements from a scan into integers called “CT numbers” or “Hounsfield units”, which are used to control the brightness of a corresponding pixel on a display.
The term “generation” is used in CT to describe successively commercially available types of CT systems utilizing different modes of scanning motion and x-ray detection. More specifically, each generation is characterized by a particular geometry of scanning motion, scanning time, shape of the x-ray beam, and detector system.
The first generation utilized a single pencil x-ray beam and a single scintillation crystal-photomultiplier tube detector for each tomographic slice. After a single linear motion or traversal of the x-ray tube and detector, during which time 160 separate x-ray attenuation or detector readings are typically taken, the x-ray tube and detector are rotated through 1 degree and another linear scan is performed to acquire another view. This is repeated typically to acquire 180 views.
A second generation of CT systems was developed to shorten the scanning times by gathering data more quickly. In these units a modified fan beam is utilized, which may include anywhere from three to 52 individual collimated x-ray beams and an equal number of detectors. Individual beams resemble the single beam of a first generation scanner. However, a collection of from three to 52 of these beams contiguous to one another allows multiple adjacent cores of tissue to be examined simultaneously. The configuration of these contiguous cores of tissue resembles a fan, with the thickness of the fan material determined by the collimation of the beam and, in turn, determining the slice thickness. Because of the angular difference of each beam relative to the others, several different angular views through the body slice are examined simultaneously. Superimposed on this is a linear translation or scan of the x-ray tube and detectors through the body slice. Thus, at the end of a single translational scan, during which time 160 readings may be made by each detector, the total number of readings obtained is equal to the number of detectors times 160. The increment of angular rotation between views can be significantly larger than with a first generation unit, up to as much as 36 degrees. Thus, the number of distinct rotations of the scanning apparatus can be significantly reduced, with a coincidental reduction in scanning time. By gathering more data per translation, fewer translations are needed.
To obtain even faster scanning times it is necessary to eliminate the complex translational-rotational motion of the first two generations. Third generation scanners therefore use a much wider, “divergent” fan beam. In fact, the angle of the beam may be wide enough to encompass most or all of an entire patient section without the need for a linear translation of the x-ray tube and detectors. As in the first two generations, the detectors, now in the form of a large array, are rigidly aligned relative to the x-ray beam, and there are no translational motions at all. The tube and detector array are synchronously rotated about the patient through an angle of 180-360 degrees. Thus, there is only one type of motion, allowing a much faster scanning time to be achieved. After one rotation, a single tomographic section is obtained.
Fourth generation scanners also feature a divergent fan beam similar to the third generation CT system. As before, the x-ray tube rotates through 360 degrees without having to make any translational motion. However, unlike in the other scanners, the detectors are not aligned rigidly relative to the x-ray beam. In this system only the x-ray tube rotates. A large ring of detectors are fixed in an outer circle in the scanning plane. The necessity of rotating only the tube, but not the detectors, allows faster scan time.
With the development of detector technology, multi-detector row CT that allows simultaneous data acquisition of multiple slices has been widely used in clinical practice. The number of slices has evolved from 4 to 320, which allows extremely fast scanning speed. Each x-ray projection view becomes a cone-beam shape instead of a fan-beam shape. The image reconstruction from cone-beam data acquisition has been a challenging problem.
Exact reconstruction methods have been proposed and further developed for both a helical x-ray source trajectory and more general source trajectories. A mathematically exact and shift-invariant FBP reconstruction formula was proposed for the helical/spiral source trajectory by A. Katsevich, “Theoretically exact filtered backprojection-type inversion algorithm for spiral CT,” SIAM (Soc. Ind. Appl. Math.) J. Appl. Math. 62, 2012-2026 (2002).
Dual energy x-ray imaging systems acquire images of the subject at two different x-ray energy levels. This can be achieved with a conventional third generation CT system by alternately acquiring views using two different x-ray tube anode voltages. Alternatively, two separate x-ray sources with associated detector arrays may be operated simultaneously during a scan at two different energy levels. In either case, two registered images of the subject are acquired at two prescribed energy levels.
The measurement of an x-ray transmission map attenuated by a subject at two distinct energy bands is often used to determine material-specific information of an imaged subject. This is based upon that fact that, in general, attenuation is a function of x-ray energy according to two attenuation mechanisms: photoelectric absorption and Compton scattering. These two mechanisms differ among materials of different atomic numbers. For this reason, measurements at two energies can be used to distinguish between two different basis materials. Dual energy x-ray techniques can be used, for example, to separate bony tissue from soft tissue in medical imaging, to quantitatively measure bone density, to remove plaque from vascular images, and to distinguish between different types of kidney stones.
Currently, one of the conventional methods employed to determine the effective atomic number and density of the material from a dual energy CT measurement is described, for example, in L. A. Lehmann, et al., “Generalized Image Combinations in Dual KVP Digital Radiography,” Med Phys (1981); 8:659-667. This method is further summarized and implemented by W. A. Kalendar, et al., in “Evaluation of a prototype dual-energy computed tomographic apparatus. I. Phantom studies.” Med Phys. 1986; 13(3):334-339. In general, the linear attenuation coefficient, μ(r,E), can be expressed as a linear combination of the mass attenuation coefficients of two so-called basis materials, as follows:
                                          μ            ⁡                          (                              r                ,                E                            )                                =                                                                      (                                      μ                    ρ                                    )                                1                            ⁢                                                (                  E                  )                                ·                                                      ρ                    1                                    ⁡                                      (                    r                    )                                                                        +                                                            (                                      μ                    ρ                                    )                                2                            ⁢                                                (                  E                  )                                ·                                                      ρ                    2                                    ⁡                                      (                    r                    )                                                                                      ,                            (        1        )            
where r is the spatial location at which a measurement is made, E is the energy at which a measurement is made, ρi(r) is the decomposition coefficient of the ith basis material, and
            (              μ        ρ            )        i    ⁢      (    E    )  is the mass attenuation coefficient of the ith basis material.
This method is commonly referred to as the basis-material method. In this method, CT measurements are needed at two energy levels (high and low) to solve the two unknowns ρ1(r) and ρ2 (r). The detected signals for these two energy levels can be expressed as:
                                          I            k                    =                                    ∫                                                                                                                ⁢                                                                                S                    k                                    ⁡                                      (                    E                    )                                                  ·                                  D                  ⁡                                      (                    E                    )                                                  ·                E                ·                                  ⅇ                                      -                                          [                                                                                                                                  (                                                              μ                                ρ                                                            )                                                        1                                                    ⁢                                                                                    (                              E                              )                                                        ·                                                          L                              1                                                                                                      +                                                                                                            (                                                              μ                                ρ                                                            )                                                        2                                                    ⁢                                                                                    (                              E                              )                                                        ·                                                          L                              2                                                                                                                          ]                                                                                  ⁢                                                          ⁢                              ⅆ                E                                                    ,                            (        2        )            
where Sk(E) is the x-ray spectrum for the kth x-ray energy, D(E) is the detector response, L1=∫dl·ρ1(r), and L2=∫dl·ρ2(r), which represent the line integral of the densities of the two basis materials, respectively.
Instead of solving the above integral equation directly, the basis-material decomposition method typically uses a table lookup procedure to solve equation (2) in order to determine L1 and L2. Conventional reconstruction methods are subsequently used to produce density maps of the two basis materials. Utilizing the information contained in the density maps of the two basis materials, the linear attenuation coefficient of the subject, μ(r,E), is determined. Monochromatic images can thus be synthesized by using the linear combination suggested by Eq. (1).
Accordingly, the basis-material method is a practical method to employ in a clinical setting when using dual-energy CT. The decomposition coefficients, ρi(r), can be interpreted as components in a two-dimensional vector space, with the basis materials defining the basis vectors. The above-described basis-material method belongs to the “pre-reconstruction” class of quantitative CT methods. That is, the method is performed with raw data, or “projection space data,” prior to reconstruction.
Currently, dual-source CT (DSCT) scanners with two source-detector pairs that are 90 degrees apart are used for many dual-energy applications. However, when operating in helical mode, the projection data acquired by the two source-detector pairs are not coincident with each other. As a result, the acquired dual-energy data cannot be processed prior to image reconstruction. This presents many limitations on the quantitative evaluation of materials when operating a DSCT scanner at dual-energies and in helical mode.
DSCT scanners, with orthogonal x-ray source-detector pairs, generally force image reconstruction to occur prior to dual-energy processing, as a result of the 90 degree offset between corresponding projections in the high- and low-energy image data sets. For axial CT acquisitions, shifting of one data set by 90 degrees would allow projection space dual-energy processing, since all of the projections are coplanar. However, in helical mode, the projection data from the two sources are not aligned with any other projections at any point in the dataset due to the continuous motion of the object along the z-axis. This precludes projection space dual-energy processing and represents a major limitation in the dual-source approach to dual-energy helical CT.
Furthermore, since helical, dual-energy data cannot be readily processed prior to image reconstruction, the resultant images suffer from beam hardening errors. That is, in non-DSCT systems, once the dual-energy algorithm decomposes the data into two components of the two basis materials (or atomic number and density), monochromatic images can be constructed at any specific photon energy. These monochromatic images are substantially improved because beam-hardening errors are substantially corrected.
Therefore, it would be advantageous to have a system and method for utilizing DSCT systems, for example in helical mode or other modes, more efficiently and without the resultant images suffering from beam-hardening artifacts.